Ultrasonic imaging generates images of one or both of stationary and moving anatomy. Common modes of diagnostic ultrasound imaging include B-mode or M-mode to generate an anatomical image of internal structures from magnitude detected acoustic echoes. Multiple gate color flow mapping and single gate spectral Doppler modes are used primarily to image blood flow or tissue motion. The displays associated with these motion detection imaging modes may be overlaid on top of B-mode images. B-mode ultrasonic imaging predominantly utilizes grayscale maps that assign different display gray levels to received acoustic signal magnitudes. Colors other than gray can also be used to represent different returned magnitudes. The color flow mapping mode predominantly utilizes color maps to display motion parameters over the B-mode images. Different colors are often assigned to estimated motion parameters such as magnitude, energy, velocity, variance, and spectral magnitudes.
These many imaging modes available on an ultrasound scanner can provide valuable diagnostic information in a short time frame. Improvements to these imaging modes can facilitate shorter exam times, allowing more patients to be examined. Shorter exams enable more exams per day which can generate increased revenue for the equipment owner.
Image flash in these imaging modes can inhibit efficiency in examinations. Image flash results in an abrupt display of a large area of color or gray over the desired viewing area. Color or grayscale flashes prevent accurate analysis of flow dynamics or tissue movement. Flashes are caused by movement of the transducer, patient breathing, the heart beating, peristalsis during digestion, gas moving in the bowels, and other undesired movements near the area of interest. Effective minimization of flash artifacts may eliminate additional manipulation by a user of image display controls during an examination. The frequency of access to many buttons that control different types of signal processing filters, velocity scale settings in motion detection modes, frame rates, and other image quality parameters can be reduced with flash suppression.
Motion detection processing, including color flow processing, minimizes flashes by using higher velocity scales, shorter pulse repetition intervals (PRIs), and clutter filters with broad low frequency spectral suppression bands or stopbands. Other flash suppression techniques that may be used for B-mode or motion processing imaging modes include absolute energy or magnitude threshholding, low velocity threshholding, non-linear energy weighted temporal persistence, and non-adaptive as well as adaptive clutter or wall filtering.
In absolute energy or magnitude threshholding, parameters associated with a measured absolute signal level are not displayed if the absolute signal level exceeds a predefined threshold. This technique may erroneously suppress valid flow or tissue movement that exceeds the threshold. Also, low signal level flash may not be suppressed.
In low velocity threshholding, signal parameters indicative of motion are not displayed if they originate from an area with a velocity below a velocity threshold. This technique fails to eliminate high velocity flashes, such as during color Doppler energy ("CDE") imaging where velocity signals are sometimes aliased for increased sensitivity. Further, valid flow signals with low velocities are removed along with the flash signals.
In non-linear energy weighted temporal persistence, filter coefficients of a persistence filter are weighted as a function of the input energy level. High energy signals result in a reduction of the weight of the filter coefficient while low energy signals result in an increase of the weight of the filter coefficient. High energy signals are minimized, assuming that flash is associated with high energy and that flash is relatively short in duration. This technique fails to eliminate flash, but merely reduces the flash. Further, with this technique, lower energy flashes may not be reduced.
In non-adaptive clutter filtering, a clutter or wall filter with sufficient low frequency stopband rejection eliminates some flash since flash is often composed of low frequency signals. This technique fails to comprehensively suppress flash where the high amplitudes of flash signals exceed the filter's stopband rejection levels. Further, flash signals that have spectral bandwidths greater than the filter's stopband bandwidths are not suppressed.
In adaptive clutter filtering, a clutter or wall filter is applied to the acquired signal as a function of the signal's characteristics. Clutter and possibly flash signals are suppressed by a notch filter determined from the mean frequency, energy, and/or variance estimates of the unfiltered in-phase and quadrature ("I/Q") representation of the acquired signal. Another technique uses a mean frequency estimate of the unfiltered I/Q samples to demodulate the I/Q samples so that the dominant clutter or flash is at the DC level where a clutter filter has the greatest signal rejection. These techniques require the clutter or flash to be estimated accurately and positioned within a stopband of the filter which is not always possible. A third technique applies an Nth order polynomial model to the input I/Q signals and subtracts the model signal from the I/Q signals to help suppress clutter or flash. These adaptive techniques can also fail for the same reasons stated for the non-adaptive clutter filtering techniques.
U.S. Pat. No. 5,152,292 discloses an algorithm that identifies flashes based on the absolute energy and velocity for each location and selectively suppresses the display of the velocity estimate. Locations with a velocity below a threshold and/or energy above a threshold are identified as containing flash. The number of locations containing flash in a frame or along a display line are determined and compared to a rejection level. The locations containing flash are suppressed if the number of flashes exceeds the rejection level. This technique fails to suppress weaker flashes. Also, this technique can suppress signals that represent a desired flow that should not be suppressed. Further, this technique fails to suppress flashes that do not have low velocities. For example, CDE values are often derived from scale settings that produce velocity aliasing and cause the flash to appear at high velocities.
U.S. Pat. No. 5,782,769 discloses an algorithm for suppressing large excursions of a Doppler signal using a min-max and/or max-min filter applied across frames at distinct spatial locations. An N-spatial location sliding window on a single Doppler parameter data stream identifies the minimum value within the window to produce a data stream of minimum values. A second N-spatial location sliding window is applied to the "minimum" data stream to identify a data stream of maximum values. The difference between the current value of the original data stream and this last data stream is compared to a predetermined threshold. When the threshold is exceeded, the value from the last data stream replaces the current value. Otherwise, the original data is not altered. This removes large positive excursions. Large negative excursions can be eliminated by reversing the order of the minimum and maximum identification acts. When the length of the sliding window does not match the underlying flash characteristics, this technique fails to suppress some flash and removes flow signals.